Class/Object

com.salesforce.op.stages.impl.tuning

DataCutter

Related Docs: object DataCutter | package tuning

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class DataCutter extends Splitter with DataCutterParams

Instance that will make a holdout set and prepare the data for multiclass modeling Creates instance that will split data into training and test set filtering out any labels that don't meet the minimum fraction cutoff or fall in the top N labels specified.

Linear Supertypes
DataCutterParams, Splitter, SplitterParams, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. DataCutter
  2. DataCutterParams
  3. Splitter
  4. SplitterParams
  5. Params
  6. Serializable
  7. Serializable
  8. Identifiable
  9. AnyRef
  10. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new DataCutter(uid: String = UID[DataCutter])

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Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. final def $[T](param: Param[T]): T

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    Attributes
    protected
    Definition Classes
    Params

  4. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. final def clear(param: Param[_]): DataCutter.this.type

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    Definition Classes
    Params

  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  8. def copy(extra: ParamMap): DataCutter

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    Definition Classes
    DataCutter → Params

  9. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params

  10. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params

  11. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  12. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  13. def explainParam(param: Param[_]): String

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    Definition Classes
    Params

  14. def explainParams(): String

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    Definition Classes
    Params

  15. final def extractParamMap(): ParamMap

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    Definition Classes
    Params

  16. final def extractParamMap(extra: ParamMap): ParamMap

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    Definition Classes
    Params

  17. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  18. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params

  19. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any

  20. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params

  21. def getMaxLabelCategories: Int

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    Definition Classes
    DataCutterParams

  22. def getMinLabelFraction: Double

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    Definition Classes
    DataCutterParams

  23. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params

  24. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params

  25. def getReserveTestFraction: Double

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    Definition Classes
    SplitterParams

  26. def getSeed: Long

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    Definition Classes
    SplitterParams

  27. final def hasDefault[T](param: Param[T]): Boolean

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    Definition Classes
    Params

  28. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  29. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  30. final def isDefined(param: Param[_]): Boolean

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    Definition Classes
    Params

  31. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  32. final def isSet(param: Param[_]): Boolean

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    Definition Classes
    Params

  33. final val maxLabelCategories: IntParam

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    Definition Classes
    DataCutterParams

  34. final val minLabelFraction: DoubleParam

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    Definition Classes
    DataCutterParams

  35. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  36. final def notify(): Unit

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    Definition Classes
    AnyRef

  37. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  38. lazy val params: Array[Param[_]]

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    Definition Classes
    Params

  39. def prepare(data: Dataset[Row]): ModelData

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    function to use to prepare the dataset for modeling eg - do data balancing or dropping based on the labels

    function to use to prepare the dataset for modeling eg - do data balancing or dropping based on the labels

    data

    first column must be the label as a double

    returns

    Training set test set

    Definition Classes
    DataCutter → Splitter

  40. final val reserveTestFraction: DoubleParam

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    Fraction of data to reserve for test Default is 0.1

    Fraction of data to reserve for test Default is 0.1

    Definition Classes
    SplitterParams

  41. final val seed: LongParam

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    Seed for data splitting

    Seed for data splitting

    Definition Classes
    SplitterParams

  42. final def set(paramPair: ParamPair[_]): DataCutter.this.type

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    Attributes
    protected
    Definition Classes
    Params

  43. final def set(param: String, value: Any): DataCutter.this.type

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    Attributes
    protected
    Definition Classes
    Params

  44. final def set[T](param: Param[T], value: T): DataCutter.this.type

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    Definition Classes
    Params

  45. final def setDefault(paramPairs: ParamPair[_]*): DataCutter.this.type

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    Attributes
    protected
    Definition Classes
    Params

  46. final def setDefault[T](param: Param[T], value: T): DataCutter.this.type

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    Attributes
    protected
    Definition Classes
    Params

  47. def setMaxLabelCategories(value: Int): DataCutter.this.type

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    Definition Classes
    DataCutterParams

  48. def setMinLabelFraction(value: Double): DataCutter.this.type

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    Definition Classes
    DataCutterParams

  49. def setReserveTestFraction(value: Double): DataCutter.this.type

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    Definition Classes
    SplitterParams

  50. def setSeed(value: Long): DataCutter.this.type

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    Definition Classes
    SplitterParams

  51. def split[T](data: Dataset[T]): (Dataset[T], Dataset[T])

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    Function to use to create the training set and test set.

    Function to use to create the training set and test set.

    returns

    (dataTrain, dataTest)

    Definition Classes
    Splitter

  52. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef

  53. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any

  54. val uid: String

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    Definition Classes
    Splitter → Identifiable

  55. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  56. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  57. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from DataCutterParams

Inherited from Splitter

Inherited from SplitterParams

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

param

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